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Speech based Parkinson’s Disease Detection using Machine Learning Techniques: A Survey

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s41870-024-02058-8openalex-snapshot

A novel WO-ANT: whale-ant optimization algorithm for detection of Parkinson’s disease

inferredcites →https://doi.org/10.1016/j.bbe.2019.05.005openalex-snapshot

Parkinson disease prediction using intrinsic mode function based features from speech signal

inferredcites →https://doi.org/10.1038/s41598-024-64004-9openalex-snapshot

Detection of Parkinson disease using multiclass machine learning approach

inferredcites →https://doi.org/10.1109/access.2018.2851382openalex-snapshot

Deep Multi-Layer Perceptron Classifier for Behavior Analysis to Estimate Parkinson’s Disease Severity Using Smartphones

inferredcites →https://doi.org/10.1109/access.2019.2936564openalex-snapshot

Deep Learning-Based Parkinson’s Disease Classification Using Vocal Feature Sets

inferredcites →https://doi.org/10.1109/access.2020.2974008openalex-snapshot

A Spectrogram-Based Deep Feature Assisted Computer-Aided Diagnostic System for Parkinson’s Disease

inferredcites →https://doi.org/10.1109/access.2021.3051432openalex-snapshot

A Deep Learning Based Method for Parkinson’s Disease Detection Using Dynamic Features of Speech

inferredcites →https://doi.org/10.1109/access.2024.3506433openalex-snapshot

Speech as a Biomarker for Disease Detection

inferredcites →https://doi.org/10.1109/asru.2011.6163978openalex-snapshot

Detection of persons with Parkinson's disease by acoustic, vocal, and prosodic analysis

inferredcites →https://doi.org/10.1109/coginfocom50765.2020.9237877openalex-snapshot

Articulation correctness measurement of Parkinson's disease using low resource-intensitve segmentation methods

inferredcites →https://doi.org/10.1109/ebbt.2019.8741725openalex-snapshot

A Hybrid Approach to Parkinson Disease Classification Using Speech Signal: The Combination of SMOTE and Random Forests

inferredcites →https://doi.org/10.1109/embc.2017.8037317openalex-snapshot

Feature analysis of dysphonia speech for monitoring Parkinson's disease

inferredcites →https://doi.org/10.1109/embc44109.2020.9176193openalex-snapshot

Parkinson’s Disease Classification using Pitch Synchronous Speech Segments and Fine Gaussian Kernels based SVM

inferredcites →https://doi.org/10.1109/icassp40776.2020.9053770openalex-snapshot

Using X-Vectors to Automatically Detect Parkinson’s Disease from Speech

inferredcites →https://doi.org/10.1109/icassp49660.2025.10890110openalex-snapshot

Graph Neural Networks for Parkinson’s Disease Detection

inferredcites →https://doi.org/10.1109/iceeot.2016.7755419openalex-snapshot

Prediction of Parkinson's disease using speech signal with Extreme Learning Machine

inferredcites →https://doi.org/10.1109/iciss49785.2020.9316078openalex-snapshot

Classification of Parkinson's Disease using Speech Attributes with Parametric and Nonparametric Machine Learning Techniques

inferredcites →https://doi.org/10.1109/iraset48871.2020.9092228openalex-snapshot

Parkinson’s Disease Identification using KNN and ANN Algorithms based on Voice Disorder

inferredcites →https://doi.org/10.1109/jtehm.2019.2940900openalex-snapshot

Automated Detection of Parkinson’s Disease Based on Multiple Types of Sustained Phonations Using Linear Discriminant Analysis and Genetically Optimized Neural Network

inferredcites →https://doi.org/10.1109/lifetech52111.2021.9391925openalex-snapshot

Residual-Network -Based Deep Learning for Parkinson's Disease Classification using Vocal Datasets

inferredcites →https://doi.org/10.21437/interspeech.2024-2205openalex-snapshot

It’s Time to Take Action: Acoustic Modeling of Motor Verbs to Detect Parkinson’s Disease

inferredcites →https://doi.org/10.3390/math12101575openalex-snapshot

Ensemble Machine Learning Approach for Parkinson’s Disease Detection Using Speech Signals

inferredcites →https://doi.org/10.36227/techrxiv.172114874.42384008/v1openalex-snapshot

Deep Learning based prediction and monitoring of Parkinson's Disease using Voice Data

inferredcites →https://doi.org/10.5755/j01.itc.53.2.33368openalex-snapshot

Improved Glowworm Swarm Optimization for Parkinson’s Disease Prediction Based on Radial Basis Functions Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1016/j.ijmedinf.2026.106587openalex-snapshot

Machine learning-based detection of Parkinson’s disease from facial expressions, hand movements, speech, and gait with general-purpose equipment: a systematic review

inferred← citeshttps://doi.org/10.1109/gcon69192.2026.11648419openalex-snapshot

Explainable Machine Learning for Parkinson’s Disease Detection from Speech Signals: A Comparative Evaluation of Classical Models

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